Master Data Management (herein MDM) in known forms quickly and reliably creates a unified view of enterprise data from multiple sources. As known in prior art, MDM can uniquely identify each instance of a business element (customer, product, account, etc.) and represent these instances using a standardized data model. Creating a master data environment enables organizations to provide a single source of truth around which enterprise systems can be synchronized. MDM in one form requires extracting key data from diverse operational environments to create a system of record files, establishing links to keep that system and operational system files synchronized, and providing fast access across all operational systems to the master data without degrading operational performance. Efforts are being made to provide a viable software solution in an enterprise-wide master data management system for harmonizing, storing and managing master data over time. Some proposed software approaches attempt to increase the consistency and accuracy of corporate performance reporting by enabling business people to collaboratively control and manage master data in a workflow-driven web-based environment. Different types of master data include product, customer, supplier, employee, chart of accounts, key performance indicator, brand, and more. When effectively implemented, MDM provides a consistent context against which business performance can be measured.
In spite of efforts to provide useful master data management software, master data in an enterprise is often duplicated and managed in multiple systems, making it difficult to create consolidated views of business performance across the enterprise. This is particularly common in enterprises which regularly undergo mergers and acquisitions; which introduce, retire, buy and sell product lines; that open and close locations; and that operate under different and changing regulatory environments across corporate divisions or geographic regions. This inconsistency makes it an arduous task to gain consolidated views of enterprise performance, or compare results across the organization.
Current solutions in master data management are based on architectures that are:                Optimized for a specific master data type (e.g. Customer/product) or specific master data use cases.        Single centralized repository.        Tightly coupled to specific technology.        
The implementation of current solutions adversely impacts enterprise deployment of MDM at least for the following reasons:                Difficulties in sharing and use of master data across the broader enterprise.        A single centralized repository is impractical in enterprise deployments where there is a wide range of latency and availability requirements.        Solution architectures require adoption of a complete technology stack—often impractical or too expensive for extended enterprise deployment.        
Master data is a critical component of any IT system. The IT landscape in any large or medium size organization usually has a number of disparate IT systems that need the same master data. Each IT system maintains a local store of master data that is required for its operation. This leads to redundant master data across IT systems that are typically out of synchronization with respect to each other. This results in suboptimal decisions and processes that use the available inaccurate master data.
There is therefore need for providing improved architecture for management of master data across repositories, data formats and applications in an enterprise.